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          Mysql引擎Innodb
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        <p>Innodb引擎，是Mysql能够在如今这个分布式时代依旧闪亮在舞台上的重要原因。即使闪亮如Postgresql的数据库，依旧还是没Mysql流行。但是，如果抓住一个服务端开发，问他</p>
<ul>
<li>Mysql的架构是什么样的？Mysql如何兼容不同引擎？</li>
<li>数据库的物理数据是由Mysql管理还是引擎管理？</li>
<li>跑SQL的时候选择哪个索引是由Innodb决定还是有Mysql决定？</li>
</ul>
<p>很多coder可能都回答不上来。这么造成什么样的结果，万一有一天需要升级Innodb，对于开发根本不知道哪些优化了哪些并没有提升。</p>
<a id="more"></a>

<h2 id="Mysql架构"><a href="#Mysql架构" class="headerlink" title="Mysql架构"></a>Mysql架构</h2><p>我们先总体的来看下Mysql + Innodb的架构，如图：<br><img src="/Innodb.png" width="100%" height="100%" alt="Innodb"/></p>
<p>我们可以发现Mysql和数据引擎是完全分离的，Mysql是通过API的方式来调用数据引擎的。这就让我联想到了Solr和Lucene的关系，Lucene为Solr提供了倒排索引的类库支持，而一些Solr的语法都是由Solr来实现。如果使用Solr你想查询name为dandan的信息，你可以使用Solr的语法:</p>
<figure class="highlight java"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">name:dandan</span><br></pre></td></tr></table></figure>
<p>而其实Solr通过解析器将Solr语句进行解析，解析成语法树，通过理解语法树来使用API来调用Lucene</p>
<figure class="highlight java"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br></pre></td><td class="code"><pre><span class="line">Query query = <span class="keyword">new</span> TermQuery(<span class="keyword">new</span> Term(<span class="string">&quot;name&quot;</span>, <span class="string">&quot;dandan&quot;</span>));</span><br><span class="line">Directory directory = FSDirectory.open(file.toPath());</span><br><span class="line">DirectoryReader directoryReader = DirectoryReader.open(directory);</span><br><span class="line">IndexSearcher indexSearcher = <span class="keyword">new</span> IndexSearcher(directoryReader);</span><br><span class="line">TopDocs topDocs = indexSearcher.search(query, <span class="number">100</span>);</span><br></pre></td></tr></table></figure>
<p>类似的Mysql也是这个道理，SQL的语法部分都是由Mysql来支持。对于一些索引的选择，我们都知道Innodb可以建立多个索引，那么选择索引的工作其实是由Mysql来实现的。但你发现你的索引不生效的时候，这个应该抄家伙问候Mysql而不是Innodb。</p>
<h2 id="Innodb的特性"><a href="#Innodb的特性" class="headerlink" title="Innodb的特性"></a>Innodb的特性</h2><p>讲完了整体的架构，还得来说说Innodb带给Mysql的特性。</p>
<ul>
<li>内存池（Buffer Pool）</li>
<li>MVCC (锁)</li>
<li>B+Tree 索引</li>
</ul>
<h3 id="内存池"><a href="#内存池" class="headerlink" title="内存池"></a>内存池</h3><p>在Mysql的架构中可以看到，我画了大大的一块内存池，因为这个内存池太重要了。我们都知道磁盘的速度在计算机中是一个很大的瓶颈，如果每一次都是直接往磁盘中写数据，那就慢炸了。所以，无论是HBase、Solr Cloud，还是今天的主角Innodb都会提供内存池。因为内存池的存在，又要保证不丢失数据，所以就会存在HLog、Transcation Log、Redo Log。</p>
<table>
<thead>
<tr>
<th align="left">HBase</th>
<th align="left">Solr Cloud</th>
<th align="left">Innodb</th>
</tr>
</thead>
<tbody><tr>
<td align="left">HLog</td>
<td align="left">Transcation Log</td>
<td align="left">Redo Log</td>
</tr>
</tbody></table>
<p>这些内存池，不仅提供了插入的缓存，还提供了查询的缓存。每次查询都是先从内存中查询，在到磁盘上找数据。忽然间你会发现数据库很多的特性都是相同的，即使底层的设计理念不同，但是在某些设计上是一样的。</p>
<p>不同的是，Mysql作为一个高性能的数据库，还提供了一些关键特性，类似“插入缓冲”、“两次写”、“自适应哈希索引”、“异步IO”、“刷新邻接页”。这里由于篇幅有限就不拓展了，可以查看《Mysql技术内幕-Innodb存储引擎》这本书。</p>
<h3 id="MVCC-多版本并发操作"><a href="#MVCC-多版本并发操作" class="headerlink" title="MVCC 多版本并发操作"></a>MVCC 多版本并发操作</h3><p>为了提升数据库的性能，对于多版本的数据操作是很有必要的。简单的来讲，就是事务只能够看到时间戳之前的数据，这样保证了在一个事务中所有的操作都是针对同一版本的数据。但是当多个版本同时进行数据的操作修改的时候，就需要使用Lock来保证数据的ACID中的I的特性。</p>
<ul>
<li>Gap Lock</li>
<li>Next Key Lock</li>
<li>Record Lock</li>
</ul>
<p>锁住的颗粒是依次减少的，推荐大家看下这篇Blog，简单易懂。</p>
<blockquote>
<p><a href="http://www.cnblogs.com/zhoujinyi/p/3435982.html">http://www.cnblogs.com/zhoujinyi/p/3435982.html</a></p>
</blockquote>
<h3 id="B-Tree-索引"><a href="#B-Tree-索引" class="headerlink" title="B+Tree 索引"></a>B+Tree 索引</h3><p>Innodb最为出名的都是B+Tree索引了，为什么是Tree而不是Hash？Hash虽然快，但是数据库往往需要使用到between以及In等语法，所以折中的最优解决方案就是B+Tree了。</p>
<p>当然，还有很多小伙伴肯定分不清什么事聚簇索引和非聚簇索引。叶子节点挂载的是数据的是，聚簇索引，典型的就是Mysql主键的索引。而非聚簇索引就是叶子节点挂载的不是数据。那不是数据是什么呢？当然就是主键了，所以在Mysql中，即使命中了辅助索引，最后还是会在主键索引中查找一边。</p>
<h2 id="Mysql-优化器"><a href="#Mysql-优化器" class="headerlink" title="Mysql 优化器"></a>Mysql 优化器</h2><p>什么事优化器？很多小伙伴表示没说听说过这位大兄弟呀，纷纷表示没用过这个玩意。但是，你肯定用过EXPLAIN，那么EXPLAIN其实就是在看优化器做了什么。典型的就讲两个例子，一个是索引的选择，一个是关联的优化。</p>
<h3 id="索引选择"><a href="#索引选择" class="headerlink" title="索引选择"></a>索引选择</h3><p>但存在多个索引的时候，就需要有人来确定使用哪个索引。没错，这就是位于Mysql所做的事，记住这不是Innodb干的，而是Mysql干的。但是呢，不巧的是，索引是由数据引擎维护的，优化器怎么知道应用哪个索引呢。Innodb就提供每个索引的Cardinality，Cardinality是由Innodb提供用来展示索引中不重复的数量。意味着，Cardinality越高，那么这个索引的价值更高。Cardinality是通过Innodb采样的，隔一段时间或者符合某种条件会进行统计。</p>
<p>如果用户想要强制的使用某个索引，可以使用：</p>
<figure class="highlight sql"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">select</span> <span class="operator">*</span> <span class="keyword">from</span> t force Index(a);</span><br></pre></td></tr></table></figure>
<h3 id="关联优化"><a href="#关联优化" class="headerlink" title="关联优化"></a>关联优化</h3><p>说道优化器这块，其实最最令人头疼的是什么？当然是join了。Mysql 仅仅支持 Nested Join，对于Sort join和hash join是不支持的。</p>
<p>举个例子</p>
<figure class="highlight sql"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line"><span class="keyword">select</span> <span class="operator">*</span> <span class="keyword">from</span> A <span class="keyword">left</span> <span class="keyword">join</span> B <span class="keyword">on</span> A.id <span class="operator">=</span> B.AID</span><br></pre></td></tr></table></figure>
<p>其实在Mysql是：</p>
<figure class="highlight java"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br></pre></td><td class="code"><pre><span class="line">outer = select * from A</span><br><span class="line"><span class="keyword">for</span> (Out out: outer) &#123;</span><br><span class="line">	select * from B where B.AID = out</span><br><span class="line">&#125;</span><br></pre></td></tr></table></figure>
<p>写的比较low，但想表达的意思是，Join的语法其实和我们写的for循环没什么区别，仅仅是优化器替我们做了循环的操作。</p>
<h2 id="总结"><a href="#总结" class="headerlink" title="总结"></a>总结</h2><p>虽然写的比较零散，但是更多的是从一个服务端开发的角度来描述我眼中的Mysql。当然对于DBA大佬，对于Mysql的使用又是一个新的境界。只是希望通过此文，能帮助大家对于Mysql有个完整，清晰的概念。很多的知识内容都是来源于，《高性能Mysql》和《Mysql技术内幕-Innodb存储引擎》这两本书。这两本书很系统完善的讲解了Mysql以及Innodb的角角落落。本文仅仅是做一个总结和梳理作用，帮助大家对于Mysql有个总体的概念。</p>
<p>顺便一提，本文讲解的点，都是面试经常会考到的，不妨在仔细体会体会。</p>

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